The present invention relates to techniques for generation modulation codes using substitution rules, and more particularly, to techniques for substituting bit sequences that cause errors with bit patterns that are less likely to cause errors.
A disk drive can write data bits onto a data storage disk such as a magnetic hard disk. The disk drive can also read data bits that have been stored on a data disk. Certain sequences of data bits are difficult to write onto a disk and often cause errors during read-back of the data.
Long recorded data sequences of the same polarity are examples of data bit patterns that are prone to errors. These data sequences correspond to long sequences of binary zeros or binary ones in the NRZ (non return-to-zero) representation, or alternatively to long sequences of binary zeros in the NRZI or PR4 representations. Another example of error prone data bit patterns are long sequences of zeros in alternating positions (e.g., 0A0Bb0C0D0 . . . , where A, B, C, D may each be 0 or 1) in the PR4 representation.
Binary sequences are routinely transformed from one representation to another using precoders and inverse precoders, according to well known techniques.
It is desirable to eliminate error prone bit sequences in user input data. Eliminating error prone bit sequences ensures reliable operation of the detector and timing loops in a disk drive system. One way to eliminate error prone bit sequences is to substitute the error prone bit sequences with non-error prone bit patterns that are stored in memory in lookup tables. Lookup tables, however, are undesirable for performing substitutions of very long bit sequences, because they require a large amount of memory.
Many disk drives have a modulation encoder. A modulation encoder uses modulation codes to eliminate sequences of bits that are prone to errors.
Maximum transition run (MTR) constrained codes are one specific type of modulation code that are used in conjunction with a 1/(1+D) precoder. With respect to MTR codes, a j constraint refers to the maximum number of consecutive ones in an NRZI representation, a k constraint refers to the maximum number of consecutive zeros in an NRZI representation, and a t constraint refers to the maximum number of consecutive pairs of bits of the same value in an NRZI representation (e.g., AABBCCDDEE . . . ).
Codes that constrain the longest run of zero digits in the PR4 representation of a sequence are said to enforce a G-constraint where G is the longest allowed run of consecutive zeros. A G constrained PR4 representation is mapped to a k-constrained NRZI representation by a 1/(1+D) precoder, where k=G+1.
Codes that constrain the longest run of zero digits in alternate locations in the PR4 representation of a sequence are said to enforce an I-constraint where I is the longest run of zeros in consecutive odd or even locations. An I-constrained sequence is necessarily G-constrained with G=2I. An I constrained PR4 representation is mapped to a t-constrained NRZI representation by a 1/(1+D) precoder, where t=I.
Fibonacci codes are one example of modulation codes that are used by modulation encoders. Fibonacci codes provide an efficient way to impose modulation code constraints on recorded data to eliminate error prone bit sequences. A Fibonacci encoder maps an input number to an equivalent number representation in a Fibonacci base. A Fibonacci encoder maps an input vector with K bits to an output vector with N bits. A Fibonacci encoder uses a base with N vectors, which is stored as an N×K binary matrix. Successive application of Euclid's algorithm to the input vector with respect to the stored base gives an encoded vector of length N.
Fibonacci codes are naturally constructed to eliminate long runs of consecutive one digits. That is, Fibonacci codes are naturally constructed to enforce a MTR j-constraint. A trivial modification of the Fibonacci code is formed by inverting the encoded sequence to eliminate long runs of consecutive zero digits and enforce a G-constraint or a k-constraint. Further modifications of Fibonacci codes are known in the art to enforce a constraint on both the maximum run of ones and the maximum run of zeros. There are several types of constraint for which a Fibonacci code construction does not exist.
Therefore, it would be desirable to provide a means of extending one family of modulation encoders to enforce additional constraints. For example, Fibonacci codes that enforce a k-constraint can be extended to enforce both a k-constraint and a t-constraint.